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            <article class="content wrap" id="_content" data-uid="TensorFlow">
  
  <h1 id="TensorFlow" data-uid="TensorFlow">Namespace TensorFlow
  </h1>
  <div class="markdown level0 summary"><p>.NET Bindings for TensorFlow.</p>
</div>
  <div class="markdown level0 conceptual"></div>
  <div class="markdown level0 remarks"><p>
    This is the API documentation for the TensorFlowSharp project.
      </p></div>
    <h3 id="classes">Classes
  </h3>
      <h4><a class="xref" href="TensorFlow/TensorFlow.Adagrad.html">Adagrad</a></h4>
      <section><p>Adaptive stochastic gradient descent optimizer.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.AdaptiveOptimizer.html">AdaptiveOptimizer</a></h4>
      <section><p>The base class for all the adaptive optimizers.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.DeviceAttributes.html">DeviceAttributes</a></h4>
      <section><p>Describes the device attributes</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.MonoPInvokeCallbackAttribute.html">MonoPInvokeCallbackAttribute</a></h4>
      <section><p>This attribute can be applied to callback functions that will be invoked
            from unmanaged code to managed code.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.Optimizer.html">Optimizer</a></h4>
      <section><p>Base class for all the optimizers.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.PaddingFIFOQueue.html">PaddingFIFOQueue</a></h4>
      <section><p>A FIFOQueue that supports batching variable-sized tensors by padding.
            Port of Python implementation <a href="https://github.com/tensorflow/tensorflow/blob/b46340f40fe5e2ec9bfcd385b07cfb914055fb51/tensorflow/python/ops/data_flow_ops.py#L697">https://github.com/tensorflow/tensorflow/blob/b46340f40fe5e2ec9bfcd385b07cfb914055fb51/tensorflow/python/ops/data_flow_ops.py#L697</a></p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.QueueBase.html">QueueBase</a></h4>
      <section><p>Base class for queue implementations.
            Port of Python implementation <a href="https://github.com/tensorflow/tensorflow/blob/r1.3/tensorflow/python/ops/data_flow_ops.py">https://github.com/tensorflow/tensorflow/blob/r1.3/tensorflow/python/ops/data_flow_ops.py</a></p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.RMSProp.html">RMSProp</a></h4>
      <section><p>RMSProp: Adaptive stochastic gradient descent optimizer.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.SGD.html">SGD</a></h4>
      <section><p>Stochastic gradient descent optimizer.
            Includes support for momentum, learning rate decay, and Nesterov momentum</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFBuffer.html">TFBuffer</a></h4>
      <section><p>Holds a block of data, suitable to pass, or retrieve from TensorFlow.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFCore.html">TFCore</a></h4>
      <section><p>Contains TensorFlow fundamental methods and utility functions.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFDependencies.html">TFDependencies</a></h4>
      <section><p>TFGraph variable dependencies handle.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFDevice.html">TFDevice</a></h4>
      <section><p>Class to unset device name in the graph within using block.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFDisposable.html">TFDisposable</a></h4>
      <section><p>Base class for many TensorFlow data types that provides a common idiom to dispose and
            release resources associated with the native data types.   Generally, you do not need to use this.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFDisposableThreadSafe.html">TFDisposableThreadSafe</a></h4>
      <section><p>ase class for many TensorFlow data types that provides a common idiom to dispose and
            release resources associated with the native data types and whose unmanaged resource
            disposing can be called from a background thread (the finalizer).   Users do not 
            need to deal with this class.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFException.html">TFException</a></h4>
      <section><p>TensorFlow Exception</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFFunction.html">TFFunction</a></h4>
      <section><p>A grouping of operations with defined inputs and outputs.
            Once created and added to graphs, functions can be invoked by creating an
            operation whose operation type matches the function name.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFGraph.html">TFGraph</a></h4>
      <section><p>Represents a computation graph.  Graphs may be shared between sessions and are thread safe.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFImportGraphDefOptions.html">TFImportGraphDefOptions</a></h4>
      <section><p>Contains options that are used to control how graph importing works.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFLibrary.html">TFLibrary</a></h4>
      <section><p>Represents a dynamically loaded library of TensorFlow operations, use to load and consume TensorFlow operations from an external library.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFOperation.html">TFOperation</a></h4>
      <section><p>Represents a computation node in the graph.  Tensorflow operations are attached to a <span class="xref">Tensorflow.TFGraph</span>.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFOperationDesc.html">TFOperationDesc</a></h4>
      <section><p>Low-level TensorFlow operation builder</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFScope.html">TFScope</a></h4>
      <section><p>TFGraph name scope handle</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFSession.html">TFSession</a></h4>
      <section><p>Drives the execution of a graph</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFSession.PartialRunToken.html">TFSession.PartialRunToken</a></h4>
      <section><p>Token returned from using one of the Partial Run Setup methods from <a class="xref" href="TensorFlow/TensorFlow.TFSession.html">TFSession</a>,
            and use this token subsequently for other invocations.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFSession.Runner.html">TFSession.Runner</a></h4>
      <section><p>Use the runner class to easily configure inputs, outputs and targets to be passed to the session runner.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFSessionOptions.html">TFSessionOptions</a></h4>
      <section><p>The session options object holds configuration options that you want to use during your session, like the TensorFlow target or the configuration.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFShape.html">TFShape</a></h4>
      <section><p>Represents the shape of a tensor, it describes how many dimensions the tensor has in a given axis</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFStatus.html">TFStatus</a></h4>
      <section><p>Used to track the result of TensorFlow operations.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFTensor.html">TFTensor</a></h4>
      <section><p>TFTensor holds a multi-dimensional array of elements of a single data type.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.Variable.html">Variable</a></h4>
      <section><p>The Variable class holds the TFOutput nodes that are used to initialize, read and assign a value to a variable.</p>
</section>
    <h3 id="structs">Structs
  </h3>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFAttributeMetadata.html">TFAttributeMetadata</a></h4>
      <section><p>Low-level: this describes the tensorflow type information for an attribute in the low-level attributes used by operations.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFInput.html">TFInput</a></h4>
      <section><p>Represents a specific input of an operation.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFOutput.html">TFOutput</a></h4>
      <section><p>Represents a specific output of an operation on a tensor.</p>
</section>
    <h3 id="enums">Enums
  </h3>
      <h4><a class="xref" href="TensorFlow/TensorFlow.DeviceType.html">DeviceType</a></h4>
      <section><p>Device type</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFAttributeType.html">TFAttributeType</a></h4>
      <section><p>Low-level: Enumeration describing the types of a metadata attribute</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFCode.html">TFCode</a></h4>
      <section><p>Status code for invoking a tensorflow operation.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFDataType.html">TFDataType</a></h4>
      <section><p>The data type for a specific tensor.</p>
</section>
    <h3 id="delegates">Delegates
  </h3>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFBuffer.BufferReleaseFunc.html">TFBuffer.BufferReleaseFunc</a></h4>
      <section><p>Signature of the method that is invoked to release the data.</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFGraph.WhileConstructor.html">TFGraph.WhileConstructor</a></h4>
      <section><p>Signature of the method that will be invoked by the TFGraph.While method to construct a while loop</p>
</section>
      <h4><a class="xref" href="TensorFlow/TensorFlow.TFTensor.Deallocator.html">TFTensor.Deallocator</a></h4>
      <section><p>Signature that methods must conform to to be used to release memory that was passed to a manually allocated TFTensor</p>
</section>
</article>
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